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SEMI P43-0304 © SEMI 2004 7 • ad ditionally if clipped: region of interest, clipp ing details. 8.2.2.2 (cl ipped) feature area g ain — area in the actual (clipped) feat ure contour outsi de of the nominal (clipped) feat …

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surround(ing mask area), preferably clarified with a
drawing, will replace the pitch information.
7.23 measured feature inter-proximity error —
measured value of feature inter-proximity error, stating
as mandatory information in addition to that of
measured feature width and feature inter-proximity
error:
• the number of measurement points used per pitch
or surrounding mask area (to be more than one
measurement per pitch). If more than one
measurement per pitch is taken, then the mean
value for each pitch is used.
and as optional information:
• the measured area on the mask.
• the spatial distribution of measurement locations.
7.24 feature proximity error — total range of the
deviations between the mask feature width and the
respective target width on a range of feature widths and
on a variation of local pattern density and configuration
(i.e., of the surround) (see Figure 6c), stating as
mandatory info:
• the range of feature widths used (at mask level).
(DEFAULT is the interval from the critical
dimension to 5 times this value.)
NOTE 14: The ITRS uses a wider interval.
• all types and tones of features considered, e.g., line,
contact, space, etc. (see in Section 5 for definitions
of these terms). It is a strong recommendation to
fix on 1 tone and 1 type to reach a useful number.
DEFAULT is on lines (“line proximity error”).
• all orientations considered, e.g., horizontal and
vertical together, horizontal only, vertical only,
including other angles, horizontal-and-vertical
separately, etc.
• range of feature pitches. In more general cases an
alternative detailed description of the surround(ing
mask area), preferably clarified with a drawing,
will replace the pitch information.
7.25 measured feature proximity error — measured
value of feature proximity error, stating as mandatory
information in addition to that of measured feature
width and feature proximity error:
• the number of measurement points used per pitch
or surrounding mask area (recommendation is > 1.
Then the mean value is used).
and as optional information:
• the measured area on the mask.
• the spatial distribution of measurement locations.
8 2D Mask Qualification Terminology
8.1 Introductory Remarks
8.1.1 The 2D terminology adds onto the 1D
terminology (Section 7). The 1D errors are an inherent
part of, and affect, the 2D qualification. Section 8.2
treats 2D-qualification without considering the impact
of 1D control (Section 7). Section 8.3 will suggest how
to include consequences of feature width deviation.
8.1.2 Most 2D definitions are based on a comparison of
a nominal and an actual feature/pattern. Where
relevant, appropriate alignment of nominal and actual
feature/pattern is assumed. This will be treated in detail
in Section
8.4.
8.2 True Values
NOTE 15: Reminder: The meaning of true is described in
Section 2.2. An ideal measurement then includes the idea of
perfect alignment of nominal and actual feature (see Section
8.4).
8.2.1 feature contour — shape formed by all edges of a
feature, including external and internal edges (see Note
3 in Section 5.10). If the feature considered is clipped
,
then the edge(s) clipped by the region of interest serve
as the edge(s) of the clipped feature (Figure 7).
ROI
Figure 7
Contour (for definition see Section 8.2.1, shown as a
full line,) of a clipped feature
(region of interest in light grey; the dotted line
shows the feature contour outside ROI)
8.2.2 General Approach, Based on Area
8.2.2.1 (clipped) feature area — enclosed area defined
by the edges of the (clipped) feature, i.e., area in the
(clipped) feature contour, mentioning as mandatory
information:
• description of the nominal feature including type,
dimensional information, tone, surrounding area,
and orientation relative to the coordinate system
(described in Section 6).
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• additionally if clipped: region of interest, clipping
details.
8.2.2.2 (clipped) feature area gain — area in the actual
(clipped) feature contour outside of the nominal
(clipped) feature (see Figure 8). Additional mandatory
information:
• relative position of actual and nominal feature (see
Section 8.4).
8.2.2.2.1 Note that the value of the (clipped) feature
area gain is always positive.
Figure 8
Illustration of feature area (top: nominal feature,
center: actual feature) and bottom: feature area
gain (light gray), feature area loss (black) and
overlapping area (medium gray)
8.2.2.3 (clipped) feature area loss — (clipped) area
outside of the actual feature, still inside of the nominal
feature (see Figure 8).
8.2.2.3.1 Same mandatory information as in (clipped)
feature area gain.
8.2.2.3.2 Note that the value of the (clipped) feature
area loss is always positive.
(a)
(b)
Figure 9
Illustration that edge roughness can influence
feature area deviation, unlike feature area
difference.
(a) without edge roughness (or with severe
smoothing)
(b) with edge roughness: area gain and area loss are
larger than in case (a), but can compensate each-
other when using feature area difference
8.2.2.4 (clipped) feature area difference — (clipped)
feature area gain minus (clipped) feature area loss. This
is also equal to the (clipped) feature area of the actual
feature minus the (clipped) feature area of the nominal
feature. The value of the (clipped) feature area
difference may be positive or negative accordingly.
Same mandatory information as in (clipped) feature
area gain.
NOTE 16: This qualification parameter is recommended for
contacts or dots, because in these cases it is of relatively
minor importance where the gain and loss are situated.
8.2.2.5 absolute (clipped) feature area deviation — the
sum of the values of (clipped) feature area gain and
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(clipped) feature area loss. Note that the value of the
absolute (clipped) feature area deviation is always
positive. Same mandatory information as in (clipped)
feature area gain.
NOTE 17: This qualification parameter is recommended for
features for which it does matter where the gain and loss are
situated.
NOTE 18: This reasoning could be extended to Pattern area
gain /loss /difference /deviation if several features are present
in the region of interest.
NOTE 19: Edge roughness may influence feature area
deviation, unlike feature area difference, in which the effect
of edge roughness is filtered out by allowing the resulting area
gain and area loss to cancel out (see Figure 9).
NOTE 20: Normalized feature area, normalized feature area
gain, normalized feature area loss, normalized feature area
difference and normalized feature area deviation are defined
as the ratio between the actual value of the considered
parameter and the nominal feature area.
8.2.3 Specific Case of Corner Rounding (CR)
8.2.3.1 corner rounding — deviation of an actual
feature corner from the nominal one.
8.2.3.1.1 The definition above is qualitative, and can be
quantified in all practical cases by treating it as a
special case of feature area difference (see further in
Sections 8.2.3.2–7). Quantitative determination
requires as mandatory information:
• the designed angle (see Figure 10), DEFAULT
angle is 90 degrees.
• feature tone: dark vs. clear.
• corner type: outer vs. inner. Corner type is ambig-
uous without feature tone specified (see Figure 11).
• other features or feature corners within the
proximity range from the corner of interest,
DEFAULT is an isolated corner.
• orientation of the corner (determined by the 2
linear sections, e.g., 90^ 180, 160^ 210,…, (see
Figure 10). DEFAULT is all 4 orientations with
linear sections along X- and Y-axes (Figure 12) for
both dark and clear feature tone.
NOTE 21: The purpose of the default corners is to help the
user of this document to select representative features to
qualify, for example, the corner rounding fingerprint of a
mask making process.
Y
X
α
β
(α , β)
Figure 10
Nomenclature of Feature Corners by the Angles of
Their Linear Sections
(a)
(b)
Figure 11
Illustration of nomenclature used for feature
corners (elbow as example)
(a) dark feature; (b) clear feature;
bottom left in each sub-figure: inner corner;
top right in each sub-figure: outer corner.